Optimized placement of virtual machines on physical hosts based on user configured placement policies

ABSTRACT

Placement of virtual machines on physical hosts are based on differing initial policies and optimization policies set by a system administrator to more efficiently utilize system resources and serve the needs of different workloads. A scheduler mechanism allows a system administrator to select different initial placement policies for one or more host groups of physical hosts. The scheduler mechanism utilizes an optimizer that monitors host performance and adjusts the placement of virtual machines according to another set of optimization policies similarly selected by the system administrator for each of the host groups.

BACKGROUND

1. Technical Field

This invention generally relates to virtual machines in a computingenvironment, and more specifically relates to placement of virtualmachines on physical hosts in a computing environment based on differinginitial policies and optimization policies.

2. Background Art

Cloud computing is a common expression for distributed computing over anetwork and can also be used with reference to network-based servicessuch as Infrastructure as a Service (IaaS). IaaS is a cloud basedservice that provides physical processing resources to run virtualmachines (VMs) as a guest for different customers. The virtual machinemay host a user application or a server.

A computing environment, such as a cloud computing environment, may havea large number of physical machines that can each host one or morevirtual machines. Prior art cloud management tools allow a systemadministrator to assist in determining a specific physical host in whichto place or deploy a new virtual machine. After deployment, the cloudmanagement tools may optimize the system by moving one or more virtualmachines to a different physical host. The placement of the new virtualmachine initially and during optimization may be determined by aplacement policy selected by the system administrator.

BRIEF SUMMARY

An apparatus and method place virtual machines on physical hosts basedon differing initial policies and optimization policies set by a systemadministrator to more efficiently utilize system resources and serve theneeds of different workloads. A scheduler mechanism allows a systemadministrator to select different initial placement policies for one ormore host groups of physical hosts. The scheduler mechanism utilizes anoptimizer that monitors host performance and adjusts the placement ofvirtual machines according to another set of optimization policiessimilarly selected by the system administrator for each of the hostgroups.

The foregoing and other features and advantages of the invention will beapparent from the following more particular description of preferredembodiments of the invention, as illustrated in the accompanyingdrawings.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

The disclosure will be described in conjunction with the appendeddrawings, where like designations denote like elements, and:

FIG. 1 is a block diagram of a cloud computing node;

FIG. 2 is a block diagram of a cloud computing environment;

FIG. 3 is a block diagram of abstraction model layers;

FIG. 4 is a block diagram that illustrates a scheduler mechanism asdescribed herein that provides placement of virtual machines on physicalresources based on differing initial policies and optimization policies;

FIG. 5 is a block diagram that illustrates a simplified example ofplacing virtual machines on host computer resources based on initialpolicies;

FIG. 6 is a block diagram that illustrates a simplified example ofplacing virtual machines on host computer resources based onoptimization policies;

FIG. 7 is a flow diagram of a method for placement of virtual machineson physical resources based on differing initial policies andoptimization policies as described herein; and

FIG. 8 is a flow diagram of an example method for step 730 in FIG. 7.

DETAILED DESCRIPTION

The claims and disclosure herein provide mechanisms for placement ofvirtual machines on physical hosts based on differing initial policiesand optimization policies set by a system administrator to moreefficiently utilize system resources and serve the needs of differentworkloads. A scheduler mechanism allows a system administrator to selectdifferent initial placement policies for one or more host groups ofphysical hosts. The scheduler mechanism utilizes an optimizer thatmonitors host performance and adjusts the placement of virtual machinesaccording to another set of optimization policies similarly selected bythe system administrator for each of the host groups.

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as Follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as Follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based email). Theconsumer does not manage or control the underlying cloud infrastructureincluding network, servers, operating systems, storage, or evenindividual application capabilities, with the possible exception oflimited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as Follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forloadbalancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a block diagram of an example of a cloudcomputing node is shown. Cloud computing node 100 is only one example ofa suitable cloud computing node and is not intended to suggest anylimitation as to the scope of use or functionality of embodiments of theinvention described herein. Regardless, cloud computing node 100 iscapable of being implemented and/or performing any of the functionalityset forth hereinabove.

In cloud computing node 100 there is a computer system/server 110, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 110 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, handheld or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 110 may be described in the general context ofcomputer system executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 110 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 110 in cloud computing node100 is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 110 may include, but are notlimited to, one or more processors or processing units 120, a systemmemory 130, and a bus 122 that couples various system componentsincluding system memory 130 to processor 120.

Bus 122 represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnect (PCI) bus.

Computer system/server 110 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 110, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 130 can include computer system readable media in the formof volatile, such as random access memory (RAM) 134, and/or cache memory136.

Computer system/server 110 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 140 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 122 by one or more datamedia interfaces. As will be further depicted and described below,memory 130 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions described in more detail below.

Program/utility 150, having a set (at least one) of program modules 152,may be stored in memory 130 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 152 generally carry out the functionsand/or methodologies of embodiments of the invention as describedherein.

Computer system/server 110 may also communicate with one or moreexternal devices 190 such as a keyboard, a pointing device, a display180, a disk drive, etc.; one or more devices that enable a user tointeract with computer system/server 110; and/or any devices (e.g.,network card, modem, etc.) that enable computer system/server 110 tocommunicate with one or more other computing devices. Such communicationcan occur via Input/Output (I/O) interfaces 170. Still yet, computersystem/server 110 can communicate with one or more networks such as alocal area network (LAN), a general wide area network (WAN), and/or apublic network (e.g., the Internet) via network adapter 160. Asdepicted, network adapter 160 communicates with the other components ofcomputer system/server 110 via bus 122. It should be understood thatalthough not shown, other hardware and/or software components could beused in conjunction with computer system/server 110. Examples, include,but are not limited to: microcode, device drivers, redundant processingunits, external disk drive arrays, RAID systems, tape drives, dataarchival storage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 200 isdepicted. As shown, cloud computing environment 200 comprises one ormore cloud computing nodes 100 with which local computing devices usedby cloud consumers, such as, for example, personal digital assistant(PDA) or cellular telephone 210A, desktop computer 210B, laptop computer210C, and/or automobile computer system 210N may communicate. Nodes 100may communicate with one another. They may be grouped (not shown)physically or virtually, in one or more networks, such as Private,Community, Public, or Hybrid clouds as described hereinabove, or acombination thereof. This allows cloud computing environment 200 tooffer infrastructure, platforms and/or software as services for which acloud consumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 210A-Nshown in FIG. 2 are intended to be illustrative only and that computingnodes 100 and cloud computing environment 200 can communicate with anytype of computerized device over any type of network and/or networkaddressable connection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 200 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and the disclosure andclaims are not limited thereto. As depicted, the following layers andcorresponding functions are provided.

Hardware and software layer 310 includes hardware and softwarecomponents. Examples of hardware components include mainframes 352; RISC(Reduced Instruction Set Computer) architecture based servers 354;servers 356; blade servers 358; storage devices 360; and networks andnetworking components 362. In some embodiments, software componentsinclude network application server software 364 and database software366.

Virtualization layer 320 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers368; virtual storage 370; virtual networks 372, including virtualprivate networks; virtual applications and operating systems 374; andvirtual clients 376.

In one example, management layer 330 may provide the functions describedbelow. Resource provisioning 378 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 380provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 382 provides access to the cloud computing environment forconsumers and system administrators. Service level management 384provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 386 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA. The management layer further includes ascheduler mechanism (SM) 350 as described herein. While the SM 350 isshown in FIG. 3 to reside in the management layer 330, the SM 350actually may span other levels shown in FIG. 3 as needed.

Workloads layer 340 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 386; software development and lifecycle management 390;virtual classroom education delivery 392; data analytics processing 394;transaction processing 396 and mobile desktop 398.

As will be appreciated by one skilled in the art, aspects of thisdisclosure may be embodied as a system, method or computer programproduct. Accordingly, aspects may take the form of an entirely hardwareembodiment, an entirely software embodiment (including firmware,resident software, micro-code, etc.) or an embodiment combining softwareand hardware aspects that may all generally be referred to herein as a“circuit,” “module” or “system.” Furthermore, aspects of the presentinvention may take the form of a computer program product embodied inone or more computer readable medium(s) having computer readable programcode embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a non-transitory computer readable storage medium. A computerreadable storage medium may be, for example, but not limited to, anelectronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system, apparatus, or device, or any suitable combinationof the foregoing. More specific examples (a non-exhaustive list) of thecomputer readable storage medium would include the following: anelectrical connection having one or more wires, a portable computerdiskette, a hard disk, a random access memory (RAM), a read-only memory(ROM), an erasable programmable read-only memory (EPROM or Flashmemory), an optical fiber, a portable compact disc read-only memory(CD-ROM), an optical storage device, a magnetic storage device, or anysuitable combination of the foregoing. In the context of this document,a computer readable storage medium may be any tangible medium that cancontain, or store a program for use by or in connection with aninstruction execution system, apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Referring now to FIG. 4, a block diagram illustrates a schedulermechanism 350 (shown in FIG. 3 and introduced above) that providesplacement of virtual machines on physical resources based on differinginitial policies and optimization policies. In the illustrated example,the scheduler mechanism 350 is part of a cloud manager 410. The cloudmanager 410 may be similar to cloud managers known in the prior art butincludes the additional features of the scheduler mechanism 350 asdescribed herein. The cloud manager 410 allows a human user or systemadministrator 414 to set up and manage computer resources through a userinterface 416. The cloud manager 410 implements the cloud managementfunctions 330 described above with reference to FIG. 3. The schedulermechanism 350 includes an optimizer 412. The optimizer 412 works inconjunction with the scheduler mechanism 350. The optimizer 412 mayoperate similarly to prior art optimizers except as described hereinincludes additional features. The optimizer 412 monitors VM and hostperformance and allows the scheduler mechanism 350 to migrate VMs toother hosts according to policies set by a system administrator. Theoperation of the scheduler mechanism 350 and the optimizer 412 aredescribed further below.

Referring again to FIG. 4, the cloud manager 410 allows the systemadministrator to set up and manage hardware computer resources 420.Computer resources 420 represent computer resources such as physicalhost computer systems in a cloud computing environment. In theillustrated example, the computer resources 420 includes two host groupsof computers, host_group1 430 and host_group2 440. A host group is alogical grouping of one or more physical computer hosts (not shown inFIG. 4) of the computer resources managed by the cloud manager 410. Thecomputer resources 420 may include a large number of physical computerhosts arranged into one or more host groups. The physical computer hostsmay be located remotely from the cloud manager. A host is a physicalcomputer accessible over a network to the cloud manager. A host has ahypervisor (software) that allows the host to run one or more virtualmachines as known in the prior art. Hosts are described further below.

As shown in FIG. 4, host_group1 has initial policies 432 andoptimization policies 434. Similarly, host_group2 has initial policies442 and optimization policies 444. In FIG. 4, the initial policies432,442 and optimization policies 434, 444 are shown within theirrespective host group for illustration purposes. The initial policies432,442 and optimization policies 434, 444 are logically associated withthe respective host group as shown but may physically reside in memoryor a file assessable to the scheduler mechanism 350.

As introduced above, the scheduler mechanism 350 provides placement ofvirtual machines on physical resources based on differing initialpolicies and optimization policies set by a system administrator. Theinitial and optimization policies may be one or a combination of knownpolicies developed in the future. A few of the more common policies aregiven here as examples of policies that could be utilized by thescheduler mechanism 350 described herein.

Striping—a policy for placing a VM on a host having the fewest number ofVMs (i.e., round-robin like placement).

Packing—a policy for placing a VM on a host having the highest number ofVMs (e.g., useful to densely pack systems—typically used innon-production environments in which mission critical performance isn'talways required).

CPU Allocation Based—a policy for placing a VM on a host having thelowest percentage of its available CPU resources utilized.

Memory Allocation Based—a policy for placing a VM on a host having thelowest percentage of its available memory resources utilized.

CPU Utilization Based—a policy for placing a VM on a host having thelowest average CPU utilization over the past X units of time.

FIGS. 5 and 6 illustrate an example of placing virtual machines onphysical resources as described and claimed herein. In this example, thescheduler mechanism 350 places virtual machines using initial policies432 and optimization policies 434. As mentioned above, each host groupcontains one or more physical hosts that can host virtual machines. Inthe example illustrated in FIG. 5, host_group1 430 has host1 510 andhost2 512. Only two hosts are shown in this example for simplicity, butit is understood that an actual host group may contain any number ofphysical computer hosts. Host_group1 has four virtual machines, VM1 514,VM2 516, VM3 518 and VM4 520. Similarly, host_group2 has four virtualmachines VMS 522, VM6 524, VM7 526 and VM8 528. In this example weassume the initial policies 432 for host_group1 includes a stripingpolicy that indicates to the scheduler mechanism 350 to distribute VMsevenly to the hosts. As a result of the striping policy, the virtualmachines are placed in the host group with four VMs on each host asshown.

Again referring to FIGS. 5 and 6, after initial placement, the VMsappear as shown with four VMs on each host. The scheduler mechanism inconjunction with the optimizer 412 monitors the host performance in amanner as known in the prior art. The scheduler mechanism uses theoptimization policies for host_group1 for optimization of theperformance of the host group. If the optimizer determines a host or VMindicates unsatisfactory performance or performance below a thresholdaccording to the optimization policies 434 for host_group1 430, then theoptimizer may determine to optimize according to the optimizationpolicies 434 for host_group1. In this example, we assume that one of theoptimization policies 434 is an optimization policy to migrate VMs whencentral processing unit (CPU) capacity of a host exceeds 90%. In theillustrated example, we assume that the optimizer 412 has determinedthat host 1 410 is performing beyond a threshold. For example, theoptimizer 412 may have determined that the CPUs of host1 410 areperforming at 98% of capacity. The optimizer then determines that theCPUs of host2 512 are performing below capacity and estimates thatexcess capacity can handle the increased load of moving additional VMsto host2 512. The scheduler mechanism 350 then optimizes 530 the hostgroup by migrating VM3 518 and VM4 520 to host2 as shown in FIG. 6.

The above example in FIGS. 5 and 6 illustrates an advantage to havingdifferent initial placement policies and optimization policies. As inthe above example, the initial placement policy can be a simple policythat quickly determines an appropriate host for a virtual machine.During operation, when more information is available, the schedulermechanism can use a more detailed optimization policy to migrate virtualmachines in a more optimized placement to more efficiently utilizesystem resources and serve the needs of different workloads.

FIG. 7 illustrates a flow diagram of a method 700 for placing virtualmachines on physical resources based on differing initial policies andoptimization policies. The method 700 is presented as a series of stepsperformed by a computer software program such as the scheduler mechanism350 described above. First, create one or more host groups, which can bedone by a system administrator using a graphical user interface (step710). Set initial placement policies for each host group (step 720). Setoptimization placement policies for each host group (step 730). Steps720 and 730 can also be accomplished by allowing a system administratorto select the policies using a graphical user interface. Place virtualmachines on hosts per the initial placement policies (step 740).Optimize placement of virtual machines on hosts per the optimizationpolicies set by the administrator for each host group (step 750). Themethod is then done.

Referring now to FIG. 8, a flow diagram shows method 800 that is anexemplary method for performing step 730 in method 700. Step 720 ofmethod 700 could also be accomplished with similar steps as shown herefor step 730. The method 800 is presented as a series of steps performedby a computer software program such as the scheduler mechanism 350described above. First, provide the administrator with a selection ofpolicies (step 810), then allow the administrator to select one or moreoptimization policies for each host group (step 820). Allow theadministrator to set a threshold for the selected policies for each hostgroup (step 830). The method is done.

The claims and disclosure herein provide an apparatus and method forplacement of virtual machines on physical resources based on differinginitial policies and optimization policies selected by a systemadministrator to more efficiently utilize system resources and serve theneeds of different workloads.

One skilled in the art will appreciate that many variations are possiblewithin the scope of the claims. Thus, while the disclosure isparticularly shown and described above, it will be understood by thoseskilled in the art that these and other changes in form and details maybe made therein without departing from the spirit and scope of theclaims.

The invention claimed is:
 1. A computer-implemented method for placingvirtual machines on physical host computer systems, the methodcomprising: creating at least one host group comprising a plurality ofphysical host computer systems; allowing a system administrator to set afirst set of policies and a second set of policies for the at least onehost group that respectively indicates how to place virtual machines onthe plurality of physical host computer systems; wherein the first setof policies are initial placement policies that indicate how toinitially place virtual machines on the plurality of physical hostcomputer systems; wherein the second set of policies are optimizationplacement policies that indicate how to place virtual machines on theplurality of physical host computer systems when optimizing the physicalhost computer systems; wherein the initial placement policies are simplepolicies for quickly determining an initial host for a virtual machinethat are distinct from the more detailed optimization policies formigrating virtual machines to optimize placement; placing virtualmachines on the physical host computer systems of the at least one hostgroup according to the initial placement policies; allowing the systemadministrator to set a first threshold for the initial placementpolicies and a second threshold for the optimization placement policies;monitoring performance of the physical host computer systems of the atleast one host group; and optimizing placement of the virtual machineson the physical host computer systems of the at least one host groupwhen the performance meets the second threshold of the optimizationplacement policies by migrating at least one of the virtual machines toa different one of the physical host computer systems.
 2. The method ofclaim 1 wherein a system administrator sets the initial placementpolicies for the at least one host group and sets the optimizationplacement policies for the at least one host group using a graphicaluser interface.
 3. The method of claim 1 wherein steps for performingthe method are part of a management layer of a cloud computingenvironment.
 4. The method of claim 1 wherein the optimization placementpolicies includes one or more of the following policies: striping,packing, computer processing unit allocation based, and memoryallocation based.
 5. The method of claim 1 wherein the systemadministrator is provided with a selection of policies to allow thesystem administrator to select one or more initial placement policiesfor each host group.
 6. The method of claim 1 wherein the systemadministrator is provided with a selection of policies to allow thesystem administrator to select one or more optimization placementpolicies for each host group.